An improved lasso regression model for evaluating the efficiency of intervention actions in a system reliability analysis
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-020-05537-8.pdf
Reference56 articles.
1. Yazdi M, Adesina KA, Korhan O, Nikfar F (2019) Learning from fire accident at bouali sina petrochemical complex plant. J Fail Anal Prev. https://doi.org/10.1007/s11668-019-00769-w
2. Aleixandre-Tudó JL, Alvarez I, García MJ, Lizama V, Aleixandre JL (2015) Application of multivariate regression methods to predict sensory quality of red wines. Czech J Food Sci 33:217–227. https://doi.org/10.17221/370/2014-CJFS
3. Hesamian G, Akbari MG (2019) Fuzzy Lasso regression model with exact explanatory variables and fuzzy responses. Int J Approx Reason 115:290–300. https://doi.org/10.1016/j.ijar.2019.10.007
4. Yazdi M (2019a) A perceptual computing—based method to prioritize intervention actions in the probabilistic risk assessment techniques. Qual Reliab Eng Int. https://doi.org/10.1002/qre.2566
5. Fan J, Li R (2001) Variable selection via nonconcave penalized. J Am Stat Assoc 96:1348–1360
Cited by 42 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. SCMs: Systematic Conglomerated Models for Audio Cough Signal Classification;Algorithms;2024-07-08
2. Research on internal leakage detection of the ball valves based on stacking ensemble learning;Measurement Science and Technology;2024-06-21
3. Bayesian Fusion of Degradation and Failure Time Data for Reliability Assessment of Industrial Equipment Considering Individual Differences;Processes;2024-01-26
4. A comprehensive resilience assessment framework for hydrogen energy infrastructure development;International Journal of Hydrogen Energy;2024-01
5. ACCURATE PREDICTION OF DRILL BIT PENETRATION RATE IN ROCK USING SUPERVISED MACHINE LEARNING TECHNIQUES BASE ON LABORATORY TEST DATA;Rudarsko-geološko-naftni zbornik;2024
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3